1 citations · 1 across the 5 of their papers we have counts for
8 papers
Riemannian Optimization over Symmetric Positive Definite Matrices with the Alpha-Procrustes Geometry
Derun Zhou, Keisuke Yano, Mahito Sugiyama
In Riemannian optimization, it is well known that the condition number of the Riemannian Hessian at an optimum strongly influences the asymptotic convergence behavior of optimizati…
From DPPs to -DPPs: identifiability analysis via spectral decomposition
Hideitsu Hino, Keisuke Yano
We study the geometry of determinantal point processes (DPPs) through the spectral decomposition . The spectrum governs the cardinality distribution via element…
Feature Starvation as Geometric Instability in Sparse Autoencoders
Faris Chaudhry, Keisuke Yano, Anthea Monod
Sparse autoencoders (SAEs) are used to disentangle the dense, polysemantic internal representations of large language models (LLMs) into interpretable, monosemantic concepts. Howev…
On robustness of Spectral Rényi divergence
Tetsuya Takabatake, Keisuke Yano
This paper studies a specific class of statistical divergences for spectral densities of time series: the spectral -Rényi divergences, which include the Itakura-Saito divergen…
Trajectory-Restricted Optimization Conditions and Geometry-Aware Linear Convergence
Faris Chaudhry, Anthea Monod, Keisuke Yano
Linear convergence of first-order methods is typically characterized by global optimization conditions whose constants reflect worst-case geometry of the ambient space. In high-dim…
Empirical Bayes Predictive Density Estimation under Covariate Shift in Large Imbalanced Linear Mixed Models
Abir Sarkar, Gourab Mukherjee, Keisuke Yano
We study empirical Bayes (EB) predictive density estimation in linear mixed models (LMMs) with large number of units, which induce a high dimensional random effects space. Focusing…